Exploratory Analysis
Tiago Lopes
Peak Power Output
Two variations of the vertical jump - Squat Jump (SJ) Counter Movement Jump (CMJ)
Variables of interest: Flight Time (FT) and Peak Power Output (PPO).
50 SIM
## [1] "Flight Time Quick Look + Distribution, CMJ + SJ"
##
## Shapiro-Wilk normality test
##
## data: JTFT50$Flight.Time
## W = 0.95528, p-value = 0.08662## [1] "p > 0.05 - normally distributed"## [1] "SJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: SJ$PRE and SJ$POST
## t = 1.3375, df = 10, p-value = 0.2107
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -11.62335 46.53244
## sample estimates:
## mean of the differences
## 17.45455## [1] "CMJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: CMJ$PRE and CMJ$POST
## t = 1.1055, df = 10, p-value = 0.2948
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.32638 48.48275
## sample estimates:
## mean of the differences
## 16.07818## [1] "Peak Power Output Quick Look + Distribution, CMJ + SJ"
##
## Shapiro-Wilk normality test
##
## data: JTPPO50$Peak.Power
## W = 0.9685, p-value = 0.2675## [1] "p > 0.05 - normally distributed"## [1] "SJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: SJ$PRE and SJ$POST
## t = 1.2823, df = 10, p-value = 0.2287
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -172.4506 640.0245
## sample estimates:
## mean of the differences
## 233.7869## [1] "CMJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: CMJ$PRE and CMJ$POST
## t = 1.1746, df = 10, p-value = 0.2674
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -199.8825 645.6185
## sample estimates:
## mean of the differences
## 222.868## [1] 1.0071887 0.9773456 1.0283129 1.0585645 1.0180800 NaN 0.9908181
## [8] 0.9994497 0.9790670 1.0269253 1.0390204 0.9918734 NaN NaN##
## Paired t-test
##
## data: EUR50$PRE and EUR50$POST
## t = -0.40547, df = 10, p-value = 0.6937
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.02988052 0.02067978
## sample estimates:
## mean of the differences
## -0.004600368## [1] 1.010604## [1] 1.015205100 SIM
## [1] "Flight Time Quick Look + Distribution, CMJ + SJ"
##
## Shapiro-Wilk normality test
##
## data: JTFT100$Flight.Time
## W = 0.94732, p-value = 0.0265## [1] "p < 0.05 - not normally distributed"## [1] "SJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: SJ$PRE and SJ$POST
## t = 0.51513, df = 11, p-value = 0.6167
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.63325 26.79825
## sample estimates:
## mean of the differences
## 5.0825## [1] "CMJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: CMJ$PRE and CMJ$POST
## t = 0.23551, df = 11, p-value = 0.8181
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -16.92808 20.98474
## sample estimates:
## mean of the differences
## 2.028333## [1] "Peak Power Output Quick Look + Distribution, CMJ + SJ"
##
## Shapiro-Wilk normality test
##
## data: JTPPO100$Peak.Power
## W = 0.97305, p-value = 0.3065## [1] "p > 0.05 - normally distributed"## [1] "SJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: SJ$PRE and SJ$POST
## t = -0.99327, df = 11, p-value = 0.3419
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -542.9198 205.2713
## sample estimates:
## mean of the differences
## -168.8243## [1] "CMJ paired t.test no significant difference between measurments"##
## Paired t-test
##
## data: CMJ$PRE and CMJ$POST
## t = -0.97351, df = 11, p-value = 0.3512
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -538.5386 208.2353
## sample estimates:
## mean of the differences
## -165.1517##
## Paired t-test
##
## data: EUR100$PRE and EUR100$POST
## t = 0.13237, df = 11, p-value = 0.8971
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.02977120 0.03358127
## sample estimates:
## mean of the differences
## 0.001905035## [1] 1.013399## [1] 1.013257BLOOD LACTATE
Measured Throughout Innings: Pre, PowerPlay, Middle, Post
Change in Lactate as innings progresses?
50 SIM
## [1] "Quick look"
## [1] "Remove Outliers of incorrect collection: PRE >2 and all Phases >16"
## [1] "ANOVA effect of phase on [Lactate]"## Df Sum Sq Mean Sq F value Pr(>F)
## LT50$Phase 3 107.3 35.77 4.441 0.0113 *
## Residuals 28 225.5 8.05
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## [1] "p < 0.05 significant effect of phases on lactate"
## [1] "Post-Hoc Test: Tukeys HSD"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = LT50$Lactate ~ LT50$Phase)
##
## $`LT50$Phase`
## diff lwr upr p adj
## Power Play-Pre 3.533333 -0.6514693 7.718136 0.1209904
## Middle-Pre 5.173333 1.1718966 9.174770 0.0075079
## Post-Pre 4.370833 0.1860307 8.555636 0.0381441
## Middle-Power Play 1.640000 -2.0355543 5.315554 0.6207545
## Post-Power Play 0.837500 -3.0368744 4.711874 0.9342102
## Post-Middle -0.802500 -4.4780543 2.873054 0.9323978
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lactate ~ Phase + (1 | Subject.ID)
## Data: LT50
##
## REML criterion at convergence: 143.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.4180 -0.6372 -0.0020 0.6043 2.5422
##
## Random effects:
## Groups Name Variance Std.Dev.
## Subject.ID (Intercept) 2.331 1.527
## Residual 5.645 2.376
## Number of obs: 32, groups: Subject.ID, 11
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.630 1.116 27.731 1.461 0.155327
## PhasePower Play 3.637 1.321 20.674 2.753 0.012032 *
## PhaseMiddle 5.082 1.261 20.655 4.032 0.000619 ***
## PhasePost 4.098 1.321 20.674 3.101 0.005476 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) PhsPwP PhsMdd
## PhasePwrPly -0.688
## PhaseMiddle -0.727 0.599
## PhasePost -0.688 0.574 0.599
## (Intercept) PhasePower Play PhaseMiddle PhasePost
## 1.630466 3.637262 5.082245 4.097682100 SIM
## [1] "QUICK LOOK"
## [1] "ANOVA: effect of Phase on [Lactate]"## Df Sum Sq Mean Sq F value Pr(>F)
## LT100$Phase. 3 217.2 72.40 8.754 0.000106 ***
## Residuals 46 380.5 8.27
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 2 observations deleted due to missingness## [1] "p < 0.05 significant effect of phases on lactate"## [1] "Post-Hoc Test: Tukeys HSD"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = LT100$Lactate ~ LT100$Phase.)
##
## $`LT100$Phase.`
## diff lwr upr p adj
## Power Play-Pre 3.5307692 0.5240438 6.537495 0.0155020
## Middle-Pre 4.9833333 1.9146071 8.052060 0.0004530
## Post-Pre 5.1500000 2.0812737 8.218726 0.0002853
## Middle-Power Play 1.4525641 -1.6161622 4.521290 0.5915256
## Post-Power Play 1.6192308 -1.4494955 4.687957 0.5018572
## Post-Middle 0.1666667 -2.9628323 3.296166 0.9989643## [1] "Remove Outliers of incorrect collection: PRE >2 and all Phases >16"## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## LT100$Phase. 3 217.2 72.40 8.754 0.000106 ***
## Residuals 46 380.5 8.27
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## [1] "Post Hoc"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = LT100$Lactate ~ LT100$Phase.)
##
## $`LT100$Phase.`
## diff lwr upr p adj
## Power Play-Pre 3.5307692 0.5240438 6.537495 0.0155020
## Middle-Pre 4.9833333 1.9146071 8.052060 0.0004530
## Post-Pre 5.1500000 2.0812737 8.218726 0.0002853
## Middle-Power Play 1.4525641 -1.6161622 4.521290 0.5915256
## Post-Power Play 1.6192308 -1.4494955 4.687957 0.5018572
## Post-Middle 0.1666667 -2.9628323 3.296166 0.9989643
## [1] "Subject.ID" "Phase." "Lactate"
HEART RATE
Recorded throughout the innings at the end of each over
50 SIM
## [1] "Quick Look"
## [1] "Applied linear model"
##
## Call:
## lm(formula = HR50$Heart.Rate ~ HR50$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -40.938 -13.446 0.093 15.003 43.171
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 125.3600 3.2724 38.31 < 2e-16 ***
## HR50$Over 2.5782 0.3361 7.67 1.74e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 18.7 on 156 degrees of freedom
## (18 observations deleted due to missingness)
## Multiple R-squared: 0.2738, Adjusted R-squared: 0.2692
## F-statistic: 58.83 on 1 and 156 DF, p-value: 1.736e-12## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## HR50$Over 1 20572 20572 58.83 1.74e-12 ***
## Residuals 156 54552 350
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 18 observations deleted due to missingness
100 SIM
## [1] "Quick look"
## [1] "Applied Linear model"
##
## Call:
## lm(formula = HR100$Heart.Rate ~ HR100$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -47.985 -12.440 0.502 15.188 36.387
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 133.6712 3.4729 38.490 < 2e-16 ***
## HR100$Over 2.3141 0.3614 6.404 2.84e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 18.37 on 124 degrees of freedom
## (50 observations deleted due to missingness)
## Multiple R-squared: 0.2485, Adjusted R-squared: 0.2425
## F-statistic: 41.01 on 1 and 124 DF, p-value: 2.841e-09## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## HR100$Over 1 13845 13845 41.01 2.84e-09 ***
## Residuals 124 41863 338
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 50 observations deleted due to missingness
CHANGE IN MASS
Measured both with + w/o kit (pads, gloves etc.) pre and post simulation
50 SIM
## [1] "Quick Look"
## [1] "Change in weight with kit on - paired t.test"##
## Paired t-test
##
## data: w_kit$PRE and w_kit$POST
## t = 5.6973, df = 10, p-value = 0.0001991
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.3653472 0.8346528
## sample estimates:
## mean of the differences
## 0.6## [1] "Change in weight without kit - paired t.test"##
## Paired t-test
##
## data: wo_kit$PRE and wo_kit$POST
## t = 6.4061, df = 10, p-value = 7.771e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.4150278 0.8576995
## sample estimates:
## mean of the differences
## 0.6363636## [1] "Significant change in weight between pre + post measures with + w/o kit"100 SIM
## [1] "Quick Look"
## [1] "Change in weight with kit on - paired t.test"##
## Paired t-test
##
## data: w_kit$PRE and w_kit$POST
## t = 7.1285, df = 10, p-value = 3.185e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.3624646 0.6920808
## sample estimates:
## mean of the differences
## 0.5272727## [1] "Change in weight without kit - paired t.test"##
## Paired t-test
##
## data: wo_kit$PRE and wo_kit$POST
## t = 10.198, df = 11, p-value = 6.076e-07
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.6992195 1.0841139
## sample estimates:
## mean of the differences
## 0.8916667## [1] "Significant change in weight between pre + post measures with + w/o kit"MUSCULAR OUTPUT
Singles and doubles measured throughout simulation. One off-strike triple in both sims - not analyzed
Change in sprint time as innings progresses, seperated into on/off strike and run type for analysis.
50 SIM
## [1] "Quick Look"
## [1] "On Strike Singles"## [1] "linear model"
##
## Call:
## lm(formula = onsingle$Time ~ onsingle$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7976 -0.3944 -0.1409 0.1413 2.6212
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.36922 0.10770 21.998 < 2e-16 ***
## onsingle$Over 0.03574 0.01030 3.471 0.000617 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5742 on 236 degrees of freedom
## Multiple R-squared: 0.04857, Adjusted R-squared: 0.04454
## F-statistic: 12.05 on 1 and 236 DF, p-value: 0.0006165## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## onsingle$Over 1 3.97 3.972 12.05 0.000617 ***
## Residuals 236 77.81 0.330
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## [1] "Significant effect of over # on sprint times"## [1] "On Strike Doubles"## [1] "linear model"
##
## Call:
## lm(formula = ondouble$Time ~ ondouble$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2136 -0.3720 -0.1442 0.1852 2.3594
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.48519 0.20893 11.895 <2e-16 ***
## ondouble$Over 0.02280 0.02004 1.138 0.258
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5554 on 96 degrees of freedom
## Multiple R-squared: 0.0133, Adjusted R-squared: 0.003022
## F-statistic: 1.294 on 1 and 96 DF, p-value: 0.2581## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## ondouble$Over 1 0.399 0.3992 1.294 0.258
## Residuals 96 29.614 0.3085## [1] "No significant effect of over # on sprint times"## [1] "Off-Strike Singles"## [1] "Linear model"
##
## Call:
## lm(formula = offsingle$Time ~ offsingle$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.60047 -0.24172 -0.06895 0.15486 2.00748
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.354077 0.070988 33.162 <2e-16 ***
## offsingle$Over 0.013649 0.007017 1.945 0.0532 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4074 on 190 degrees of freedom
## Multiple R-squared: 0.01953, Adjusted R-squared: 0.01437
## F-statistic: 3.784 on 1 and 190 DF, p-value: 0.05322## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## offsingle$Over 1 0.628 0.6282 3.784 0.0532 .
## Residuals 190 31.540 0.1660
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## [1] "No significant effect of over # on sprint times"## [1] "Off-Strike Doubles"
## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## offdouble$Over 1 0.056 0.05639 0.192 0.664
## Residuals 40 11.765 0.29412## [1] "No significant effect of over # on sprint times"100 SIM
## [1] "Quick Look"
## [1] "On-Strike Singles"## [1] "Linear Model"
##
## Call:
## lm(formula = onsingle$Time ~ onsingle$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8780 -0.3033 -0.1146 0.1818 1.9991
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.591662 0.053930 48.056 <2e-16 ***
## onsingle$Over 0.011317 0.005669 1.996 0.0467 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4431 on 337 degrees of freedom
## Multiple R-squared: 0.01169, Adjusted R-squared: 0.008755
## F-statistic: 3.985 on 1 and 337 DF, p-value: 0.04671## [1] "ANOVA"##
## Call:
## lm(formula = onsingle$Time ~ onsingle$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8780 -0.3033 -0.1146 0.1818 1.9991
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.591662 0.053930 48.056 <2e-16 ***
## onsingle$Over 0.011317 0.005669 1.996 0.0467 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4431 on 337 degrees of freedom
## Multiple R-squared: 0.01169, Adjusted R-squared: 0.008755
## F-statistic: 3.985 on 1 and 337 DF, p-value: 0.04671## [1] "Significant effect of over # on sprint times"
##
## Call:
## lm(formula = ondouble$Time ~ ondouble$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.4253 -0.2835 -0.1083 0.1733 1.4818
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.5696963 0.2792008 9.204 3.14e-14 ***
## ondouble$Over 0.0008768 0.0235745 0.037 0.97
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3794 on 81 degrees of freedom
## Multiple R-squared: 1.708e-05, Adjusted R-squared: -0.01233
## F-statistic: 0.001383 on 1 and 81 DF, p-value: 0.9704## Df Sum Sq Mean Sq F value Pr(>F)
## ondouble$Over 1 0.00 0.0002 0.001 0.97
## Residuals 81 11.66 0.1440## [1] "No Significant effect of over # on sprint times"## [1] "Off-Strike Singles"## [1] "Linear Model"
##
## Call:
## lm(formula = offsingle$Time ~ offsingle$Over)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.49578 -0.20521 -0.06421 0.17102 2.59091
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.449e+00 4.856e-02 50.430 <2e-16 ***
## offsingle$Over 8.598e-05 5.257e-03 0.016 0.987
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3123 on 241 degrees of freedom
## Multiple R-squared: 1.11e-06, Adjusted R-squared: -0.004148
## F-statistic: 0.0002675 on 1 and 241 DF, p-value: 0.987## [1] "ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## offsingle$Over 1 0.0 0.00003 0 0.987
## Residuals 241 23.5 0.09752## [1] "No Significant effect of over # on sprint times"## [1] "Off-Strike Doubles"
## Df Sum Sq Mean Sq F value Pr(>F)
## offdouble$Over 1 0.004 0.00420 0.046 0.831
## Residuals 36 3.281 0.09114## [1] "No Significant effect of over # on sprint times"PSYCHOPHYSICAL - Rating of Perceived Exertion
Central RPE (Cardiovascular) + Local RPE (Legs) recorded at the end of every over
50 SIM
## [1] "Quick Look"
## [1] "Central RPE ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## Central$Over 1 671.4 671.4 79.07 9.43e-16 ***
## Residuals 167 1417.9 8.5
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness## [1] "Post Hoc Tukeys HSD"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Central$Score ~ Central$Phase)
##
## $`Central$Phase`
## diff lwr upr p adj
## Middle-Close Inn. -0.6981132 -2.080754 0.6845274 0.4583633
## PowerPlay-Close Inn. -4.1563342 -5.482974 -2.8296944 0.0000000
## PowerPlay-Middle -3.4582210 -4.784861 -2.1315812 0.0000000
## [1] "Local RPE ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## Local$Over 1 850.6 850.6 107.8 <2e-16 ***
## Residuals 167 1318.0 7.9
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness## [1] "Post Hoc Tukeys HSD"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Local$Score ~ Local$Phase)
##
## $`Local$Phase`
## diff lwr upr p adj
## Middle-Close Inn. -1.471698 -2.824010 -0.1193867 0.0292936
## PowerPlay-Close Inn. -4.862234 -6.159773 -3.5646951 0.0000000
## PowerPlay-Middle -3.390536 -4.688075 -2.0929970 0.0000000
100 SIM
## [1] "Quick Look"
## [1] "Central RPE ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## Central$Over 1 888.3 888.3 99.23 <2e-16 ***
## Residuals 202 1808.3 9.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness## [1] "Post Hoc Tukeys HSD"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Central$Score ~ Central$Phase)
##
## $`Central$Phase`
## diff lwr upr p adj
## Middle-Close Inn. -1.250000 -2.54655 0.04654995 0.0614652
## PowerPlay-Close Inn. -4.476151 -5.72047 -3.23183305 0.0000000
## PowerPlay-Middle -3.226151 -4.47047 -1.98183305 0.0000000
## [1] "Local RPE ANOVA"## Df Sum Sq Mean Sq F value Pr(>F)
## Local$Over 1 753.2 753.2 152.2 <2e-16 ***
## Residuals 202 1000.0 5.0
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness## [1] "Post Hoc Tukeys HSD"## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = Local$Score ~ Local$Phase)
##
## $`Local$Phase`
## diff lwr upr p adj
## Middle-Close Inn. -1.546875 -2.525646 -0.5681038 0.0007213
## PowerPlay-Close Inn. -4.235197 -5.174539 -3.2958561 0.0000000
## PowerPlay-Middle -2.688322 -3.627664 -1.7489811 0.0000000
## [1] "Difference between central + local?"PREFRONTAL CORTEX IMAGING (FNIR)
Pre + Post measures during CogState testing. HBO - Oxygenated HGB
HBR - Deoxygenated HGB
HBT - Total HGB (HBO + HBR) OXY - Oxygenation (HBO - HBR).
CogState Battery
GMT - Groton Maze Learning Task
ONB - One Back Card memory
TWB - Two Back Card memory
50 SIM
## [1] "Quick Look"
## [1] "Lots of outliers. not altered for remaining stats"## [1] "Averaged all optodes accross headband and determined average value for each task from markers in data"
## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"## Df Sum Sq Mean Sq F value Pr(>F)
## avgHBO$Phase 1 11.6 11.577 1.068 0.307
## avgHBO$Task 2 2.4 1.208 0.111 0.895
## avgHBO$Phase:avgHBO$Task 2 29.6 14.804 1.366 0.266
## Residuals 44 477.0 10.841
## 1 observation deleted due to missingness
## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"## Df Sum Sq Mean Sq F value Pr(>F)
## avgHBR$Phase 1 13.8 13.802 1.226 0.274
## avgHBR$Task 2 1.4 0.705 0.063 0.939
## avgHBR$Phase:avgHBR$Task 2 18.2 9.114 0.809 0.452
## Residuals 44 495.5 11.260
## 1 observation deleted due to missingness100 SIM
## [1] "Quick Look"
## [1] "Lots of outliers. not altered for remaining stats"## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"
## Df Sum Sq Mean Sq F value Pr(>F)
## avgHBO$Phase 1 96.78 96.78 16.135 0.000334 ***
## avgHBO$Task 2 3.16 1.58 0.263 0.770063
## avgHBO$Phase:avgHBO$Task 2 21.22 10.61 1.769 0.186810
## Residuals 32 191.93 6.00
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"## Df Sum Sq Mean Sq F value Pr(>F)
## avgHBR$Phase 1 51.4 51.39 3.865 0.058 .
## avgHBR$Task 2 4.6 2.32 0.175 0.841
## avgHBR$Phase:avgHBR$Task 2 5.2 2.61 0.197 0.822
## Residuals 32 425.4 13.29
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1CogState
GMT - ter (total # errors lower is better), cmv (correct moves) (speed accuracy trade off)
ONB - lmn (speed), acc (accuracy)
TWB - lmn (speed), acc (accuracy)
50 + 100 TO DO: 50 vs 100 comparisons (normal dist only)